On the identification of multivariate correlated unobserved components models

Abstract

"This paper analyses identification for multivariate unobserved components models in which the innovations to trend and cycle are correlated. We address order and rank criteria as well as potential non-uniqueness of the reduced-form VARMA model. Identification is shown for lag lengths larger than one in case of a diagonal vector autoregressive cycle. We also discuss UC models with common features and with cycles that allow for dynamic spillovers." (Author's abstract, IAB-Doku) ((en))

Cite article

Trenkler, C. & Weber, E. (2015): On the identification of multivariate correlated unobserved components models. (University of Mannheim. Department of Economics. Working Paper 15-12), Mannheim, 14 p.